Face recognition at the Netherlands Institute for Sound and Vision – Is it really Harder, Better, Faster, Stronger
NISV implemented speaker detection and thesaurus label term extraction in 2015 in an effort to reduce time spent on manual annotation and to increase the amount of structured and fine grained access points for media professionals (the broadcasters) into our daily ingested programs. In 2019 face recognition has been thrown into the mix, trying to make automatic annotation “Harder, Better, Faster, Stronger”. Two years later it’s time to check the status: how well does it work, what’s the quality and quantity, what do our users think about it, what about the challenges on both technological and ethical aspects, and how does NISV apply it compared to other archives that might have similar challenges.
INA Facial recognition: Trombinos
We introduce Trombinos, a face database management system. It allows the user to navigate, cure and expand efficiently a large-scale dataset of faces, thanks to its integrated face recognition model. The database contains both face images coming from archived french TV shows, as well as face images obtained through image search engines. It already contains 62 million identified faces belonging to 70 thousand individuals, as well as 540 millions faces yet to be identified. Trombinos helps users to efficiently navigate this database, to recognize someone based on a picture, to retrieve their occurrences amongst the archived TV shows based on their name, and to manually enrich or correct the existing annotations. Our system facilitates human-machine interaction ; by identifying similar looking faces, Trombinos allows the users to validate them by batch and hence to annotate a large number of faces easily. Furthermore, Trombinos learns from the users feedback to improve its face recognition performances in real time, and in turn to facilitate the future annotations of the user in a virtuous circle. Using Trombinos, a single user can easily assign hundreds of thousands of faces to their correct identities in just a few minutes. While still in continuous development, Trombinos is already used regularly by 5 users at INA to annotate the database.
A look back at the use of facial recognition and other AI techniques at the RTS
AI was introduced and used at RTS for automatic metadata extraction a few years ago. This presentation is an opportunity to look back at the use of some of these tools, in particular facial recognition and visual search, and to discuss their impact in terms of process and changing practices.